publication . Article . Conference object . 2011

Enrichment analysis of genetic association in genes and pathways by aggregating signals from both rare and common variants

Wei Yang;
Open Access English
  • Published: 01 Nov 2011 Journal: BMC Proceedings, volume 5, issue Suppl 9, pages S52-S52 (eissn: 1753-6561, Copyright policy)
  • Publisher: BioMed Central
Abstract
<p>Abstract</p> <p>New high-throughput sequencing technologies have brought forth opportunities for unbiased analysis of thousands of rare genomic variants in genome-wide association studies of complex diseases. Because it is hard to detect single rare variants with appreciable effect sizes at the population level, existing methods mostly aggregate effects of multiple markers by collapsing the rare variants in genes (or genomic regions). We hypothesize that a higher level of aggregation can further improve association signal strength. Using the Genetic Analysis Workshop 17 simulated data, we test a two-step strategy that first applies a collapsing method in a ge...
Subjects
free text keywords: Proceedings, Medicine, R, Science, Q, General Biochemistry, Genetics and Molecular Biology, General Medicine, Gene sets, Genetic association, Multiple markers, Bioinformatics, Gene, Population, education.field_of_study, education, Genetic analysis, Signal strength, business.industry, business
Funded by
NIH| Genetic Analysis of Common Diseases: An Evaluation
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01GM031575-22
  • Funding stream: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
,
NIH| VARIABLE SELECTION IN GENETIC EPIDEMIOLOGICAL STUDIES OF CARDIOVASCULAR DISEASES
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1R01HL091028-01A1
  • Funding stream: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE
,
NIH| Genetic Determinants of the LVH Phenotype
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01HL071782-02
  • Funding stream: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE

Li, B, Leal, SM. Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. Am J Hum Genet. 2008; 83: 311-321 [OpenAIRE] [PubMed] [DOI]

Madsen, BE, Browning, SR. A groupwise association test for rare mutations using a weighted sum statistic. PLoS Genet. 2009; 5: e1000384 [OpenAIRE] [PubMed] [DOI]

Subramanian, A, Tamayo, P, Mootha, VK, Mukherjee, S, Ebert, BL, Gillette, MA, Paulovich, A, Pomeroy, SL, Golub, TR, Lander, ES. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005; 102: 15,545-15,550

Wang, K, Li, M, Bucan, M. Pathway-based approaches for analysis of genomewide association studies. Am J Hum Genet. 2007; 81: 1278-1283 [OpenAIRE] [PubMed] [DOI]

Yang, W, Gu, CC. Variable set enrichment analysis in genome-wide association studies. Eur J Hum Genet. 2011

Dering, C, Pugh, E, Ziegler, A. Statistical analysis of rare sequence variants: an overview of collapsing methods. Genet Epidemiol. 2011; X (suppl X): X-X [OpenAIRE]

Sung, Y, Rice, T, Rao, D. Application of collapsing methods for continuous traits to GAW17 exome sequence data. BMC Proc. 2011; 5 (suppl 9): S121

Luedtke, A, Powers, S, Petersen, A, Sitarik, A, Bekmetjev, A, Tintle, N. Evaluating methods for the analysis of rare variants in sequence data. BMC Proc. 2011; 5 (suppl 9): S119

Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue